Towards artificial intelligence-enabled extracellular vesicle precision drug delivery

细胞外小泡 药物输送 纳米医学 胞外囊泡 纳米技术 计算机科学 微泡 化学 生物 材料科学 小RNA 生物化学 纳米颗粒 细胞生物学 基因
作者
Zachary Greenberg,Kiley Graim,Mei He
出处
期刊:Advanced Drug Delivery Reviews [Elsevier BV]
卷期号:199: 114974-114974 被引量:133
标识
DOI:10.1016/j.addr.2023.114974
摘要

Extracellular Vesicles (EVs), particularly exosomes, recently exploded into nanomedicine as an emerging drug delivery approach due to their superior biocompatibility, circulating stability, and bioavailability in vivo. However, EV heterogeneity makes molecular targeting precision a critical challenge. Deciphering key molecular drivers for controlling EV tissue targeting specificity is in great need. Artificial intelligence (AI) brings powerful prediction ability for guiding the rational design of engineered EVs in precision control for drug delivery. This review focuses on cutting-edge nano-delivery via integrating large-scale EV data with AI to develop AI-directed EV therapies and illuminate the clinical translation potential. We briefly review the current status of EVs in drug delivery, including the current frontier, limitations, and considerations to advance the field. Subsequently, we detail the future of AI in drug delivery and its impact on precision EV delivery. Our review discusses the current universal challenge of standardization and critical considerations when using AI combined with EVs for precision drug delivery. Finally, we will conclude this review with a perspective on future clinical translation led by a combined effort of AI and EV research.
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